Figure 4

Landscape analysis can be applied to images from multiple organs with different diseases that have been classified by multiple methods and software. (a) A separate dataset of H&E stained sections of normal thyroid or thyroid showing Hashimoto’s thyroiditis (n = 10) from the GTEx Tissue Image Library were used to train a random trees classifier in QuPath after image down-scaling and cropping. Histological classes ‘cells’, ‘stroma’, ‘colloid’ and ‘space’ were used. (b) Histological pixel-class proportions for ‘cell’ and ‘colloid’ were significantly different between normal and diseased thyroid when analysed by group (individual points and median (centre line), first and third quartiles (lower and upper box limits), 1.5 × interquartile range (whiskers); p-values of Welch unpaired two-sided two-sample t-test for each metric, n = 10). (c) A full suite of landscape metrics derived from the classified images allowed segregation of cases effectively by k-means clustering.